MO401RENAL ANGINA INDEX IN ADULT CRITICAL CARE PATIENTS IN A POPULATION FROM BOGOTÁ – COLOMBIA

Abstract Background and Aims Clinical outcomes of Acute Kidney Injury (AKI) in ICU mainly depend on opportune preventive strategies. Thus, early identification of AKI is mandatory, and alternative diagnostic strategies become plausible: one of them, Renal Angina Index (RAI), described by Matsuura1, predicts the development of AKI KDIGO 2-3, at 7th day after admission to the intensive care unit according to a cut-off point >6 on a scale with a “creatinine score” (determined by the difference in serum creatinine between that at ICU admission and the first 24 hours in the ICU) and the impact of the patients medical history. 1Kidney Int Rep (2018) 3, 677-683. Our aim is to describe predictive capacity of the Renal Angina Index (RAI) in adult critical care patients in our population. Method We retrospectively selected from our Critical Care Nephrology database adult patients admitted in any of our hospital`s ICU between February to August 2020, excluding those at admission with diagnosis of AKI, serum creatinine > 2.5 mg/dl, or those receiving dialysis (acute or chronic) or kidney transplantation. We defined AKI according to KDIGO criteria. The RAI score was defined as the worst condition score multiplied by the creatinine score. The performance of the RAI score was assessed by Receiver Operating Characteristic (ROC) analysis power to detect a difference of 0.2 between the area under the curve (AUC), under the null hypothesis of AUC = 0.5 (no diagnostic accuracy). The optimal cut point was estimated with the Youden method. Results From 1204 new ICU patients, we included 372 patients (women 40.3%), with mean age 60.9 (18-98) (table 1). Main indication for ICU admission was medical conditions. Mean APACHE II was 22.9, hemodinamic support was required in 41,1% patients, mechanical ventilation in 58.6% patients and diabetes mellitus was present in 21.5% patients. AKI KDIGO 2-3 developed in 26.8% of patients. Mean creatinine at admission was statistically different in patients with AKI (CI 0.95 –0.51 - --0.15 mg/dl, p=0.0004). The requirement of hemodynamic (p = 0.003) and ventilatory support (p = 0.009), sepsis (p = 0.003), and COVID-19 (p = 0.03) were more frequent in patients who developed AKI. Renal replacement therapy was required in 39 (60%) of patients with severe AKI (incidence 10,5%). RAI cutt-off point determined by Youden method in the overall sample was 24, being significantly higher in patients who developed AKI (16.54 Vs 7.47, CI 0.95 –13.5--4.99, p <0.001). A cut-off point of 24 was required for the Best predictive capacity for severe AKI, with sensitivity, specificity, positive and negative likelihood ratio of 34%, 94%, 5.5 and 0.7 respectively. Conclusion In our population, RAI score requires a cutoff point much higher than that originally described to predict the development of severe AKI. Losing its discriminatory capacity.

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TO020POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI BY AUTOMATED DECISION SUPPORT ALGORITHMS: IMPACT ON AKI INCIDENCE

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa141.to020 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Jill Vanmassenhove ◽

Johan Steen ◽

Johan Decruyenaere ◽

Dominique Benoit ◽

Eric Adriaan J Hoste ◽

...

Keyword(s):

Big Data ◽

Decision Support ◽

Serum Creatinine ◽

Sofa Score ◽

Kidney Injury ◽

Baseline Serum ◽

Icu Admission ◽

And Gender ◽

Definition Of ◽

The Impact

Abstract Background and Aims The reported incidence of Acute Kidney Injury (AKI) at the intensive care unit (ICU) is variable. Although the Kidney Disease Improving Global Outcome (K-DIGO) improved harmonisation of this definition, there is remaining variability in the actual implementation of this AKI definition, with variable interpretation of the urinary output (UO) criterion, and of the baseline serum creatinine (Screa) criterion. This hampers progress of our understanding of the clinical concept AKI and leads to confusion and unclarity when interpreting models to predict AKI or associated outcomes. With the advent of big data and artificial intelligence based decision algorithms, this problem will only become more of interest, as the user will not know what exactly the construct AKI in the application used means and represents. Therefore, we intended to explore the impact of different interpretations of the Screa and the UO criterium as presented in the K-DIGO definition on the incidence of AKI stage 2. Method We included all patients of an electronic health data system applied in a tertiary ICU between 2013 and 2017. Sequential Organ Failure Assessment (SOFA) score was calculated, and gender, age, weight and mortality at ICU and in hospital were extracted. All serum creatinine (sCrea) values during ICU stay and hospitalisation were extracted, as were UO data, with their time stamps. In addition, all available Screa data up to 1 year before ICU admission were retrieved from a dataset external to the ICU. AKI was defined according to KDIGO stage 2, using different possible interpretations of the Screa and/or the UO criterion. For the evolution of Screa as compared to a baseline value, we sued either a value directly available to ICU staff (def 1), a presumed eGFR of 75ml/min (def 2), the first available value after admission to ICU (def 3), the lowest value during the current hospitalisation before ICU admission (def 4), the lowest value before the hospitalisation episode as found in an external dataset (def 5). For the UO criterion, we also applied two criteria in line with K-DIGO stage 2: a UO below 6ml/kg during a 12 hour block (def 6) or a UO below 0.5ml/kg/hour during each of 12 consecutive one hour intervals (def 7). Def 8 identified patients who did not comply with any of the definitions (1-7), so who had no AKI according to any definition. Definition 9 and 10 identified patients who complied with at least one out of the Screa criteria 1-5 (def 9) or out of the UO criteria (def 10). Definition 11 identified patients who complied both with at least one Screa and one UO criterium. Results Our dataset included 16433 ICU admissions (34.7% female, age 60.7±16.4 years). Overall, 8.1% of patients died at ICU, and another 5.2% during their hospitalisation. The SOFA score at admission was 6.9±4.1. The incidence of AKI according to the stage 2 definition of K-DIGO varied according to the interpretation of the diagnostic criteria from 4.3% when baseline creatinine was defined as the first ICU value, to 35.3% when the UO criterium was interpreted as a UO below 6ml/kg over a 12 hour block (fig). Only half of patients (53.7%) did not comply with any of the definitions (def 8), 10.9% and 19.7% complied with one of the Screa (def 9) OR one of the UO criteria (def 10) respectively, and 15.7% complied with both (def 11). There was substantial reclassification across the different definitions. Conclusion Unclarity on the actual interpretation of the Screa and UO criteria used in the K-DIGO definition of AKI leads to substantial differences in incidence of AKI, and also with substantial reclassification according to different definitions. This is especially concerning in an era of big data and automated decision support, as clinicians might not know which construct of AKI is actually being represented.

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Relationship Between Renal Angina Index and D-Dimer Improvement Towards Acute Kidney Injury in Covid-19 Patients in Special Isolation Room of Dr. Soetomo Hospital Surabaya

International Journal Of Scientific Advances ◽

10.51542/ijscia.v2i2.15 ◽

2021 ◽

Vol 2 (2) ◽

Author(s):

Fadhil Rasyid ◽

Bambang Pujo Semedi ◽

Arie Utariani ◽

Teuku Aswin

Keyword(s):

Acute Kidney Injury ◽

Serum Creatinine ◽

Kidney Injury ◽

World Health ◽

Isolation Room ◽

Injury Criteria ◽

Health Organization ◽

Renal Angina Index ◽

Renal Angina ◽

D Dimer

Since the World Health Organization (WHO) declared COVID-19 as pandemic in March 2020, the number of new case findings in Indonesia has continued to increase. As happened in the city of Surabaya. Even in severe cases deterioration is rapid and progressive. One of them is the high D-dimer level in COVID-19 patients, which indicates the presence of vascular thrombosis, resulting in organ failure syndromes such as Acute Kidney Injury (AKI). Such conditions clearly indicate that this virus attacks the kidneys. It is known that the prevalence of AKI is 17%, where 77% of AKI patients experienced severe COVID-19 infection, and 52% died. For this reason, this study was prepared with the aim of knowing the relationship between increased levels of D-Dimer Renal Angine Index and the incidence of Acute Kidney Injury (AKI) in COVID-19 patients in the Special Isolation Room of Dr. Soetomo Hospital Surabaya. This study was a retrospective cohort analytic observational study with a sample size of 30. The Acute Kidney Injury criteria in this study used an increase in serum creatinine ≥ 0.3 mg / dL within 48 hours, or an increase in serum creatinine ≥ 1.5 times. Through research conducted, it is known that the Renal Angina Index can be used to predict the incidence of AKI in this study with p <0.0001 and sensitivity 71%, specificity 21% (r: 0.43; strong CC> 0.3) with a limit of 7. It can be concluded that there is a relationship which is significant between the Renal Angina Index on the incidence of Acute Kidney Injury (AKI). However, there was no significant relationship between increased D-Dimer levels and the incidence of acute kidney injury.

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The impact of N-acetylcysteine and ascorbic acid in contrast-induced nephropathy in critical care patients: an open-label randomized controlled study

Critical Care ◽

10.1186/s13054-017-1862-3 ◽

2017 ◽

Vol 21 (1) ◽

Cited By ~ 9

Author(s):

Eleni Palli ◽

Demosthenes Makris ◽

John Papanikolaou ◽

Grigorios Garoufalis ◽

Irini Tsilioni ◽

...

Keyword(s):

Ascorbic Acid ◽

Critical Care ◽

Randomized Controlled Study ◽

Controlled Study ◽

Open Label ◽

Contrast Induced Nephropathy ◽

Randomized Controlled ◽

The Impact ◽

Critical Care Patients

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The impact of “early” versus “late” initiation of renal replacement therapy in critical care patients with acute kidney injury: a systematic review and evidence synthesis

Critical Care ◽

10.1186/s13054-016-1291-8 ◽

2016 ◽

Vol 20 (1) ◽

Cited By ~ 63

Author(s):

Benjamin T. Wierstra ◽

Sameer Kadri ◽

Soha Alomar ◽

Ximena Burbano ◽

Glen W. Barrisford ◽

...

Keyword(s):

Systematic Review ◽

Acute Kidney Injury ◽

Critical Care ◽

Renal Replacement Therapy ◽

Replacement Therapy ◽

Evidence Synthesis ◽

Kidney Injury ◽

Late Initiation ◽

The Impact ◽

Critical Care Patients

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Measuring Height in Recumbent Critical Care Patients

American Journal of Critical Care ◽

10.4037/ajcc2015761 ◽

2015 ◽

Vol 24 (1) ◽

pp. 41-47 ◽

Cited By ~ 9

Author(s):

Diane M. Dennis ◽

Emily E. Hunt ◽

Charley A. Budgeon

Keyword(s):

Intensive Care Unit ◽

Critical Care ◽

Intensive Care ◽

Gold Standard ◽

Ventilatory Support ◽

Whole Body ◽

Standing Height ◽

Preadmission Clinic ◽

Practice Methods ◽

Critical Care Patients

Background Estimates of the height of patients in the intensive care unit are required to adhere to clinical guidelines for drug dosages, ventilatory support, and nutrition. The gold standard of standing height cannot be used because these patients are often unconscious and recumbent. The ability of physiotherapists or dietitians to measure height in unconscious, recumbent patients has not been evaluated. Objectives To compare the accuracy of physicians, physiotherapists, and dietitians in estimating the height of recumbent critical care patients by using existing practice methods. Methods A total of 35 patients were recruited from the cardiothoracic preadmission clinic, where standing height is routinely measured by a physiotherapist. After surgery, in the intensive care unit, 1 physician, 2 physiotherapists, and 2 dietitians measured each recumbent patient’s height. Three methods were used: observation, whole-body measurement, and height estimated by using length of the forearm and the British Association for Parenteral and Enteral Nutrition normative chart. Difference from standing height was measured from zero and was compared across professions and methods, with zero indicating no difference. Results Overall, 17 physicians, 4 dietitians, and 9 physiotherapists consented to measure patients. After adjustments for method, measurements by physiotherapists did not differ significantly from the gold standard (P = .59), whereas those of physicians (P = .02) and dietitians (P < .001) did. Conclusions Physiotherapists’ measurements of supine height of recumbent critical care patients, obtained by using a nonrigid measuring tape, are more accurate than measurements obtained by physicians and dietitians.

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P0562DIFFERENT POTENTIAL INTERPRETATIONS OF CRITERIA FOR AKI WHEN USING AUTOMATED DECISION SUPPORT: IMPACT ON ASSOCIATED MORTALITY

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfaa142.p0562 ◽

2020 ◽

Vol 35 (Supplement_3) ◽

Author(s):

Wim Van Biesen ◽

Johan Steen ◽

Johan Decruyenaere ◽

Dominique Benoit ◽

Eric Adriaan J Hoste ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Serum Creatinine ◽

Mortality Risk ◽

Sofa Score ◽

Kidney Injury ◽

Baseline Serum ◽

Icu Admission ◽

Definition Of ◽

The Impact

Abstract Background and Aims The reported associated mortality risks of Acute Kidney Injury (AKI) in the intensive care unit (ICU) are variable. Although the Kidney Disease Improving Global Outcome (K-DIGO) improved harmonisation of the definition, there is remaining variability in the actual implementation of this AKI definition, with variable use of the urinary output (UO) criterion, and different interpretations of the baseline serum creatinine (Screa). This hampers progress of our understanding of the clinical concept AKI and leads to confusion and unclarity when interpreting models to predict AKI associated outcomes. With the advent of big data and artificial intelligence based decision algorithms, this problem will only become more of interest, as the user will not know what exactly the construct AKI in the application used means. Therefore, we intended to explore the impact of different interpretations of the Screa and the UO criterium as presented in the K-DIGO definition on the associated ICU mortality risk of AKI stage 2 in the ICU. Method We included all patients of an electronic health data system applied in a tertiary ICU between 2013 and 2017. Sequential Organ Failure Assessment (SOFA) score was calculated, and gender, age, weight and mortality at ICU and in hospital were extracted. All serum creatinine (sCrea) values during ICU stay and hospitalisation were extracted, as were UO data, with their time stamps. In addition, all Screa data up to 1 year before ICU admission were retrieved from a dataset external to ICU. AKI was defined according to KDIGO stage 2, using different possible interpretations of the Screa and/or the UO criterion. For the evolution of Screa as compared to a baseline value, we either used a value directly available to ICU staff (def 1), a presumed eGFR of 75ml/min (def 2), the first available value after admission to ICU (def 3), the lowest value during the current hospitalisation before ICU admission (def 4), the lowest value before the hospitalisation episode as found in an external dataset (def 5). For the UO criterion, we used either (in line with K-DIGO stage 2) a UO below 6ml/kg during a 12 hour block (def 6) or a UO below 0.5ml/kg/hour during each of 12 consecutive one hour intervals (def 7). Definition 8 and 9 identified patients who complied with at least one out of the Screa criteria 1-5 (def 8) or out of the UO criteria (def 9). Definition 10 identified patients who complied both with at least one Screa and one UO criterium. Results Our dataset comprised 16433 admissions (34.7% female, age 60.7±16.4 years). Overall, 8.1% of patients died in Intensive Care Unit (ICU). The SOFA score at admission was 6.9±4.1. The mortality risk associated with AKI according to the stage 2 definition of K-DIGO varied according to the interpretation of the diagnostic criteria (table). Most important, associated mortality risk was comparable whether a UO (RR 2.31, 95% CI 1.90-2.81) or a Screa (RR 2.00, 95% CI 1.57-2.55) criterium was used, and was highest in patients who complied with both at least one UO and one Screa criterium (RR 7.28, 95% CI 6.12-8.65). Conclusion Unclarity on the actual interpretation of the Screa and UO criteria used in the K-DIGO definition of AKI leads to substantial differences in AKI associated mortality risk. Omitting the UO criterium leads to substantial underestimation of associated risk.

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Assessment of a modified renal angina index for AKI prediction in critically ill adults

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab049 ◽

2021 ◽

Author(s):

Victor Ortiz-Soriano ◽

Shaowli Kabir ◽

Rolando Claure-Del Granado ◽

Arnold Stromberg ◽

Robert D Toto ◽

...

Keyword(s):

Risk Stratification ◽

Critically Ill ◽

External Validation ◽

Adult Patients ◽

Critically Ill Children ◽

Icu Admission ◽

Renal Angina Index ◽

Critically Ill Adults ◽

Renal Angina ◽

Ill Adults

Abstract Background The renal angina index (RAI) is a useful tool for risk stratification of acute kidney injury (AKI) in critically ill children. We evaluated the performance of a modified adult RAI (mRAI) for the risk stratification of AKI in critically ill adults. Methods We used two independent intensive care unit (ICU) cohorts: 13 965 adult patients from the University of Kentucky (UKY) and 4789 from University of Texas Southwestern (UTSW). The mRAI included: diabetes, presence of sepsis, mechanical ventilation, pressor/inotrope use, percentage change in serum creatinine (SCr) in reference to admission SCr (ΔSCr) and fluid overload percentage within the first day of ICU admission. The primary outcome was AKI Stage ≥2 at Days 2–7. Performance and reclassification metrics were determined for the mRAI score compared with ΔSCr alone. Results The mRAI score outperformed ΔSCr and readjusted probabilities to predict AKI Stage ≥2 at Days 2–7: C-statistic: UKY 0.781 versus 0.708 [integrated discrimination improvement (IDI) 2.2%] and UTSW 0.766 versus 0.696 (IDI 1.8%) (P < 0.001 for both). In the UKY cohort, only 3.3% of patients with mRAI score <10 had the AKI event, while 16.4% of patients with mRAI score of ≥10 had the AKI event (negative predictive value 96.8%). Similar findings were observed in the UTSW cohort as part of external validation. Conclusions In critically ill adults, the adult mRAI score determined within the first day of ICU admission outperformed changes in SCr for the prediction of AKI Stage ≥2 at Days 2–7 of ICU stay. The mRAI is a feasible tool for AKI risk stratification in adult patients in the ICU.

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The impact of telemetry on survival of in-hospital cardiac arrests in non-critical care patients

Resuscitation ◽

10.1016/j.resuscitation.2013.01.038 ◽

2013 ◽

Vol 84 (7) ◽

pp. 878-882 ◽

Cited By ~ 22

Author(s):

Kelby Cleverley ◽

Negareh Mousavi ◽

Lyle Stronger ◽

Kimberly Ann-Bordun ◽

Lillian Hall ◽

...

Keyword(s):

Critical Care ◽

The Impact ◽

Critical Care Patients

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Variable Creatinine Levels in Critical Care Patients: A Concerning Knowledge Gap

Journal of Clinical Medicine ◽

10.3390/jcm10081689 ◽

2021 ◽

Vol 10 (8) ◽

pp. 1689

Author(s):

Trushil Shah ◽

Madhusudhanan Narasimhan ◽

Mary Latha Rathinam ◽

Karen Relle ◽

Melanie Kim ◽

...

Keyword(s):

Critical Care ◽

Serum Creatinine ◽

Clinical Laboratory ◽

Test Accuracy ◽

Longitudinal Assessment ◽

Cross Sectional ◽

Negative Interference ◽

Survey Results ◽

Picc Line ◽

Critical Care Patients

An accurate creatinine (Cr) estimate is pivotal for the assessment of renal function. Both patient- and practice-spawned factors palliate the test accuracy of serum creatinine (sCr) and can erratically represent actual kidney function. This study evaluated the caregivers’ awareness of enzymatic serum creatinine (E-sCr) assay interfering in dopamine/dobutamine (DD)-infused patient samples and the frequency of such interference in a critical care setting. We conducted an sCr awareness survey among UT Southwestern physicians, nurses, and pharmacists. We then performed a cross-sectional E-sCr comparison against the kinetic Jaffe method using the DD-infused patient samples collected from central venous catheters (CVC), peripherally inserted central catheter (PICC) lines, and the peripheral vein (PV). We retrospectively compared the longitudinal E-sCr results of the CVC/PICC draws with the corresponding blood urea nitrogen (BUN) levels. The survey results show a significant lack of awareness among caregivers about the negative interference of DD infusions on E-sCr. Cross-sectional E-sCr assessment relative to the Jaffe method displayed a negative interference in 12% of CVC/PICC line samples (7/57 DD-infused patients) compared to none in the PV draws. A longitudinal assessment of E-sCr, BUN, and potassium (K) levels from CVC/PICC line samples further confirmed a spurious decrease for E-sCr in about 12/50 (24%) patients who did not show a concurrent BUN or K decrease. The results suggest that a direct PV sampling accompanied by clinical laboratory-directed proactive discussion/activities can foster awareness among caregivers and eschew the false E-sCr estimates in DD-infused patients.

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